Do changes in coherence always reflect changes in functional coupling?

Is Hypnotic Induction Necessary to Experience Hypnosis and Responsible for Changes in Brain Activity?

The relevance of formal hypnotic induction to the experience of trance and its neural correlates is not clear, in that hypnotizability, beliefs and expectation of hypnosis may play a major role. The aim of the study was assessing the EEG brain activity of participants with high (highs) or low hypnotizability scores (lows), aware of their hypnotizability level and informed that the session will include simple relaxation, formal hypnotic induction and neutral hypnosis. A total of 16 highs and 15 lows (according to the Stanford Hypnotic Susceptibility Scale, form A) were enrolled. Their EEGs were recorded during consecutive conditions of open/closed-eyes relaxation, hypnotic induction, neutral hypnosis and post hypnosis not interrupted by interviews. The studied variables were theta, alpha and gamma power spectral density (PSD), and the Determinism (DET) and Entropy (ENT) of the EEG signal Multidimensional Recurrence Plot (mRP). Highs reported significantly greater changes in their state of consciousness than lows across the session. The theta, alpha and gamma PSD did not exhibit condition-related changes in both groups. The Alpha PSD was larger in highs than in lows on midline sites, and the different sides/regions' theta and gamma PSD were observed in the two groups independently from conditions. ENT showed no correlation with hypnotizability, while DET positively correlated with hypnotizability during hypnosis. In conclusion, the relevance of formal hypnotic induction to the experience of trance may be scarce in highs, as they are aware of their hypnotizability scores and expecting hypnosis. Cognitive processing varies throughout the session depending on the hypnotizability level.

Theoretical considerations and supporting evidence for the primary role of source geometry on field potential amplitude and spatial extent

Field potential (FP) recording is an accessible means to capture the shifts in the activity of neuron populations. However, the spatial and composite nature of these signals has largely been ignored, at least until it became technically possible to separate activities from co-activated sources in different structures or those that overlap in a volume. The pathway-specificity of mesoscopic sources has provided an anatomical reference that facilitates transcending from theoretical analysis to the exploration of real brain structures. We review computational and experimental findings that indicate how prioritizing the spatial geometry and density of sources, as opposed to the distance to the recording site, better defines the amplitudes and spatial reach of FPs. The role of geometry is enhanced by considering that zones of the active populations that act as sources or sinks of current may arrange differently with respect to each other, and have different geometry and densities. Thus, observations that seem counterintuitive in the scheme of distance-based logic alone can now be explained. For example, geometric factors explain why some structures produce FPs and others do not, why different FP motifs generated in the same structure extend far while others remain local, why factors like the size of an active population or the strong synchronicity of its neurons may fail to affect FPs, or why the rate of FP decay varies in different directions. These considerations are exemplified in large structures like the cortex and hippocampus, in which the role of geometrical elements and regional activation in shaping well-known FP oscillations generally go unnoticed. Discovering the geometry of the sources in play will decrease the risk of population or pathway misassignments based solely on the FP amplitude or temporal pattern.

Higher hypnotic suggestibility is associated with the lower EEG signal variability in theta, alpha, and beta frequency bands

Variation of information in the firing rate of neural population, as reflected in different frequency bands of electroencephalographic (EEG) time series, provides direct evidence for change in neural responses of the brain to hypnotic suggestibility. However, realization of an effective biomarker for spiking behaviour of neural population proves to be an elusive subject matter with its impact evident in highly contrasting results in the literature. In this article, we took an information-theoretic stance on analysis of the EEG time series of the brain activity during hypnotic suggestions, thereby capturing the variability in pattern of brain neural activity in terms of its information content. For this purpose, we utilized differential entropy (DE, i.e., the average information content in a continuous time series) of theta, alpha, and beta frequency bands of fourteen-channel EEG time series recordings that pertain to the brain neural responses of twelve carefully selected high and low hypnotically suggestible individuals. Our results show that the higher hypnotic suggestibility is associated with a significantly lower variability in information content of theta, alpha, and beta frequencies. Moreover, they indicate that such a lower variability is accompanied by a significantly higher functional connectivity (FC, a measure of spatiotemporal synchronization) in the parietal and the parieto-occipital regions in the case of theta and alpha frequency bands and a non-significantly lower FC in the central region's beta frequency band. Our results contribute to the field in two ways. First, they identify the applicability of DE as a unifying measure to reproduce the similar observations that are separately reported through adaptation of different hypnotic biomarkers in the literature. Second, they extend these previous findings that were based on neutral hypnosis (i.e., a hypnotic procedure that involves no specific suggestions other than those for becoming hypnotized) to the case of hypnotic suggestions, thereby identifying their presence as a potential signature of hypnotic experience.

Phase Synchronicity of μ-Rhythm Determines Efficacy of Interhemispheric Communication Between Human Motor Cortices

The theory of communication through coherence predicts that effective connectivity between nodes in a distributed oscillating neuronal network depends on their instantaneous excitability state and phase synchronicity (Fries, 2005). Here, we tested this prediction by using state-dependent millisecond-resolved real-time electroencephalography-triggered dual-coil transcranial magnetic stimulation (EEG-TMS) (Zrenner et al., 2018) to target the EEG-negative (high-excitability state) versus EEG-positive peak (low-excitability state) of the sensorimotor μ-rhythm in the left (conditioning) and right (test) motor cortex (M1) of 16 healthy human subjects (9 female, 7 male). Effective connectivity was tested by short-interval interhemispheric inhibition (SIHI); that is, the inhibitory effect of the conditioning TMS pulse given 10-12 ms before the test pulse on the test motor-evoked potential. We compared the four possible combinations of excitability states (negative peak, positive peak) and phase relations (in-phase, out-of-phase) of the μ-rhythm in the conditioning and test M1 and a random phase condition. Strongest SIHI was found when the two M1 were in phase for the high-excitability state (negative peak of the μ-rhythm), whereas the weakest SIHI occurred when they were out of phase and the conditioning M1 was in the low-excitability state (positive peak). Phase synchronicity contributed significantly to SIHI variation, with stronger SIHI in the in-phase than out-of-phase conditions. These findings are in exact accord with the predictions of the theory of communication through coherence. They open a translational route for highly effective modification of brain connections by repetitive stimulation at instants in time when nodes in the network are phase synchronized and excitable.SIGNIFICANCE STATEMENT The theory of communication through coherence predicts that effective connectivity between nodes in distributed oscillating brain networks depends on their instantaneous excitability and phase relation. We tested this hypothesis in healthy human subjects by real-time analysis of brain states by electroencephalography in combination with transcranial magnetic stimulation of left and right motor cortex. We found that short-interval interhemispheric inhibition, a marker of interhemispheric effective connectivity, was maximally expressed when the two motor cortices were in phase for a high-excitability state (the trough of the sensorimotor μ-rhythm). We conclude that findings are consistent with the theory of communication through coherence. They open a translational route to highly effectively modify brain connections by repetitive stimulation at instants in time of phase-synchronized high-excitability states.

Focusing Attention on Muscle Exertion Increases EEG Coherence in an Endurance Cycling Task

The aim of this study was to examine EEG coherence before, during, and after time to exhaustion (TTE) trials in an endurance cycling task, as well as the effect of effort level and attentional focus (i.e., functional external, functional internal, and dysfunctional internal associative strategies-leading to Type 1, Type 2, and Type 3 performances) on brain functional connectivity. Eleven college-aged participants performed the TTE test on a cycle-ergometer with simultaneous EEG and rate of perceived exertion (RPE) monitoring. EEG data from 32 electrodes were divided into five effort level periods based on RPE values (Baseline, RPE 0-4, RPE 5-8, RPE 9-MAX, and Recovery). Within subjects RM-ANOVA was conducted to examine time to task completion across Type 1, Type 2, and Type 3 performance trials. RM-ANOVA (3 performance types × 5 effort levels) was also performed to compare the EEG coherence matrices in the alpha and beta bands for 13 pairs of electrodes (F3-F4, F3-P3, F4-P4, T7-T8, T7-P3, C3-C4, C3-P3, C4-P4, T8-P4, P3-P4, P3-O1, P4-O2, O2-O1). Significant differences were observed on TTE performance outcomes between Type 1 and Type 3, and between Type 2 and Type 3 performance states (p < 0.05), whereas Type 1 and Type 2 performance states did not differ. No significant main effects were observed on performance type (p > 0.05) for all frequency bands in any pair of electrodes of the coherence matrices. Higher EEG coherence values were observed at rest (Baseline) than during cycling (RPE 0-4, 5-8, 9-MAX) for all pairs of electrodes and EEG frequency bands irrespective of the type of performance (main effect of effort, p < 0.05). Interestingly, we observed a performance × effort interaction in C3-C4 in beta 3 band [F_{(4, 77)} = 2.62, p = 0.038] during RPE 9-MAX for Type 3 performance as compared to Type 1 and Type 2 performances. These findings may have practical implications in the development of performance optimization strategies in cycling, as we found that focusing attention on a core component of the action could stimulate functional connectivity among specific brain areas and lead to enhanced performance.

Use of phase-locking value in sensorimotor rhythm-based brain-computer interface: zero-phase coupling and effects of spatial filters

Phase-locking value (PLV) is a potentially useful feature in sensorimotor rhythm-based brain-computer interface (BCI). However, volume conduction may cause spurious zero-phase coupling between two EEG signals and it is not clear whether PLV effects are independent of spectral amplitude. Volume conduction might be reduced by spatial filtering, but it is uncertain what impact this might have on PLV. Therefore, the goal of this study was to explore whether zero-phase PLV is meaningful and how it is affected by spatial filtering. Both amplitude and PLV feature were extracted in the frequency band of 10-15 Hz by classical methods using archival EEG data of 18 subjects trained on a two-target BCI task. The results show that with right ear-referenced data, there is meaningful long-range zero-phase synchronization likely involving the primary motor area and the supplementary motor area that cannot be explained by volume conduction. Another novel finding is that the large Laplacian spatial filter enhances the amplitude feature but eliminates most of the phase information seen in ear-referenced data. A bipolar channel using phase-coupled areas also includes both phase and amplitude information and has a significant practical advantage since fewer channels required.

Beyond aphasia: Altered EEG connectivity in Broca's patients during working memory task

Broca's region and adjacent cortex presumably take part in working memory (WM) processes. Electrophysiologically, these processes are reflected in synchronized oscillations. We present the first study exploring the effects of a stroke causing Broca's aphasia on these processes and specifically on synchronized functional WM networks. We used high-density EEG and coherence analysis to map WM networks in ten Broca's patients and ten healthy controls during verbal WM task. Our results demonstrate that a stroke resulting in Broca's aphasia also alters two distinct WM networks. These theta and gamma functional networks likely reflect the executive and the phonological processes, respectively. The striking imbalance between task-related theta synchronization and desynchronization in Broca's patients might represent a disrupted balance between task-positive and WM-irrelevant functional networks. There is complete disintegration of left fronto-centroparietal gamma network in Broca's patients, which could reflect the damaged phonological loop.

Multi-Dimensional Dynamics of Human Electromagnetic Brain Activity

Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, computation, short history, and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain.

Diversity of LFPs Activated in Different Target Regions by a Common CA3 Input

Identifying the pathways contributing to local field potential (LFP) events and oscillations is essential to determine whether synchronous interregional patterns indicate functional connectivity. Here, we studied experimentally and numerically how different target structures receiving input from a common population shape their LFPs. We focused on the bilateral CA3 that sends gamma-paced excitatory packages to the bilateral CA1, the lateral septum, and itself (recurrent input). The CA3-specific contribution was isolated from multisite LFPs in target regions using spatial discrimination techniques. We found strong modulation of LFPs by target-specific features, including the morphology and population arrangement of cells, the timing of CA3 inputs, volume conduction from nearby targets, and co-activated inhibition. Jointly they greatly affect the LFP amplitude, profile, and frequency characteristics. For instance, ipsilateral (Schaffer) LFPs occluded contralateral ones, and septal LFPs arise mostly from remote sources while local contribution from CA3 input was minor. In the CA3 itself, gamma waves have dual origin from local networks: in-phase excitatory and nearly antiphase inhibitory. Also, waves may have different duration and varying phase in different targets. These results indicate that to explore the cellular basis of LFPs and the functional connectivity between structures, besides identifying the origin population/s, target modifiers should be considered.

Hypnotic induction is followed by state-like changes in the organization of EEG functional connectivity in the theta and beta frequency bands in high-hypnotically susceptible individuals

Altered state theories of hypnosis posit that a qualitatively distinct state of mental processing, which emerges in those with high hypnotic susceptibility following a hypnotic induction, enables the generation of anomalous experiences in response to specific hypnotic suggestions. If so then such a state should be observable as a discrete pattern of changes to functional connectivity (shared information) between brain regions following a hypnotic induction in high but not low hypnotically susceptible participants. Twenty-eight channel EEG was recorded from 12 high susceptible (highs) and 11 low susceptible (lows) participants with their eyes closed prior to and following a standard hypnotic induction. The EEG was used to provide a measure of functional connectivity using both coherence (COH) and the imaginary component of coherence (iCOH), which is insensitive to the effects of volume conduction. COH and iCOH were calculated between all electrode pairs for the frequency bands: delta (0.1–3.9 Hz), theta (4–7.9 Hz) alpha (8–12.9 Hz), beta1 (13–19.9 Hz), beta2 (20–29.9 Hz) and gamma (30–45 Hz). The results showed that there was an increase in theta iCOH from the pre-hypnosis to hypnosis condition in highs but not lows with a large proportion of significant links being focused on a central-parietal hub. There was also a decrease in beta1 iCOH from the pre-hypnosis to hypnosis condition with a focus on a fronto-central and an occipital hub that was greater in high compared to low susceptibles. There were no significant differences for COH or for spectral band amplitude in any frequency band. The results are interpreted as indicating that the hypnotic induction elicited a qualitative change in the organization of specific control systems within the brain for high as compared to low susceptible participants. This change in the functional organization of neural networks is a plausible indicator of the much theorized “hypnotic-state.”

Determining the true polarity and amplitude of synaptic currents underlying gamma oscillations of local field potentials

Fluctuations in successive waves of oscillatory local field potentials (LFPs) reflect the ongoing processing of neuron populations. However, their amplitude, polarity and synaptic origin are uncertain due to the blending of electric fields produced by multiple converging inputs, and the lack of a baseline in standard AC-coupled recordings. Consequently, the estimation of underlying currents by laminar analysis yields spurious sequences of inward and outward currents. We devised a combined analytical/experimental approach that is suitable to study laminated structures. The approach was essayed on an experimental oscillatory LFP as the Schaffer-CA1 gamma input in anesthetized rats, and it was verified by parallel processing of model LFPs obtained through a realistic CA1 aggregate of compartmental units. This approach requires laminar LFP recordings and the isolation of the oscillatory input from other converging pathways, which was achieved through an independent component analysis. It also allows the spatial and temporal components of pathway-specific LFPs to be separated. While reconstructed Schaffer-specific LFPs still show spurious inward/outward current sequences, these were clearly stratified into distinct subcellular domains. These spatial bands guided the localized delivery of neurotransmitter blockers in experiments. As expected, only Glutamate but not GABA blockers abolished Schaffer LFPs when applied to the active but not passive subcellular domains of pyramidal cells. The known chemical nature of the oscillatory LFP allowed an empirical offset of the temporal component of Schaffer LFPs, such that following reconstruction they yield only sinks or sources at the appropriate sites. In terms of number and polarity, some waves increased and others decreased proportional to the concomitant inputs in native multisynaptic LFPs. Interestingly, the processing also retrieved the initiation time for each wave, which can be used to discriminate afferent from postsynaptic cells in standard spike-phase correlations. The applicability of this approach to other pathways and structures is discussed.

Brisk heart rate and EEG changes during execution and withholding of cue-paced foot motor imagery

Cue-paced motor imagery (MI) is a frequently used mental strategy to realize a Brain-Computer Interface (BCI). Recently it has been reported that two MI tasks can be separated with a high accuracy within the first second after cue presentation onset. To investigate this phenomenon in detail we studied the dynamics of motor cortex beta oscillations in EEG and the changes in heart rate (HR) during visual cue-paced foot MI using a go (execution of imagery) vs. nogo (withholding of imagery) paradigm in 16 healthy subjects. Both execution and withholding of MI resulted in a brisk centrally localized beta event-related desynchronization (ERD) with a maximum at ~400 ms and a concomitant HR deceleration. We found that response patterns within the first second after stimulation differed between conditions. The ERD was significantly larger in go as compared to nogo. In contrast the HR deceleration was somewhat smaller and followed by an acceleration in go as compared to nogo. These findings suggest that the early beta ERD reflects visually induced preparatory activity in motor cortex networks. Both the early beta ERD and the HR deceleration are the result of automatic operating processes that are likely part of the orienting reflex (OR). Of interest, however, is that the preparatory cortical activity is strengthened and the HR modulated already within the first second after stimulation during the execution of MI. The subtraction of the HR time course of the nogo from the go condition revealed a slight HR acceleration in the first seconds most likely due to the increased mental effort associated with the imagery process.

Identifying the synaptic origin of ongoing neuronal oscillations through spatial discrimination of electric fields

Although intracerebral field potential oscillations are commonly used to study information processing during cognition and behavior, the cellular and network processes underlying such events remain unclear. The limited spatial resolution of standard single-point recordings does not clarify whether field oscillations reflect the activity of one or many afferent presynaptic populations. However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials. Here we review recent insights that help disentangle certain pathway-specific activities. Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations. These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

Brain integration as a driver for quality management success

Purpose

In this paper, research leading to quality management success is examined, elaborated, and highlighted in a new profound way by focusing on the most fundamental aspect of the human dimension, the brain. The purpose is to examine the relationship between brain functioning and quality management success. In this examination, the role of core values, profound organizational learning and values of quality management are explained.

Design/methodology/approach

The paper builds on a conceptual review of research in the areas of quality management success, values of quality management, core values and neurophysiology with focus on brain integration.

Findings

The relation of core values with brain functioning is described based on previous research. A framework with logical steps from brain integration, via core values, quality management values and quality management practices to quality management success is developed.

Research limitations/implications

The paper adds to the understanding of the role brain integration has for success in quality management efforts. A limitation is that it only builds on previous research.

Practical implications

The findings provide a deeper understanding of quality management success and should thus be valuable for quality managers and leaders striving for excellence for their organisations.

Originality/value

The importance and crucial role of brain integration for quality management success has not been elaborated in the literature of quality management before.

Fatigue-induced increase in intracortical communication between mid/anterior insular and motor cortex during cycling exercise

In the present study, intracortical communication between mid/anterior insular and motor cortex was investigated during a fatiguing cycling exercise. From 16 healthy male subjects performing a constant-load test at 60% peak oxygen consumption (VO(2peak)) until volitional exhaustion, electroencephalography data were analysed during repetitive, artefact-free periods of 1-min duration. To quantify fatigue-induced intracortical communication, mean intra-hemispheric lagged phase synchronization between mid/anterior insular and motor cortex was calculated: (i) at the beginning of cycling; (ii) at the end of cycling; and (iii) during recovery cycling. Results revealed significantly increased lagged phase synchronization at the end of cycling, which returned to baseline during recovery cycling after subjects' cessation of exercise. Following previous imaging studies reporting the mid/anterior insular cortex as an essential instance processing a variety of sensory stimuli and signalling forthcoming physiological threat, our results provide further evidence that during a fatiguing exercise this structure might not only integrate and evaluate sensory information from the periphery, but also act in communication with the motor cortex. To the best of our knowledge, this is the first study to empirically demonstrate that muscle fatigue leads to changes in interaction between structures of a brain's neural network.

Ketamine-induced oscillations in the motor circuit of the rat basal ganglia

Oscillatory activity can be widely recorded in the cortex and basal ganglia. This activity may play a role not only in the physiology of movement, perception and cognition, but also in the pathophysiology of psychiatric and neurological diseases like schizophrenia or Parkinson's disease. Ketamine administration has been shown to cause an increase in gamma activity in cortical and subcortical structures, and an increase in 150 Hz oscillations in the nucleus accumbens in healthy rats, together with hyperlocomotion.We recorded local field potentials from motor cortex, caudate-putamen (CPU), substantia nigra pars reticulata (SNr) and subthalamic nucleus (STN) in 20 awake rats before and after the administration of ketamine at three different subanesthetic doses (10, 25 and 50 mg/Kg), and saline as control condition. Motor behavior was semiautomatically quantified by custom-made software specifically developed for this setting.Ketamine induced coherent oscillations in low gamma (~ 50 Hz), high gamma (~ 80 Hz) and high frequency (HFO, ~ 150 Hz) bands, with different behavior in the four structures studied. While oscillatory activity at these three peaks was widespread across all structures, interactions showed a different pattern for each frequency band. Imaginary coherence at 150 Hz was maximum between motor cortex and the different basal ganglia nuclei, while low gamma coherence connected motor cortex with CPU and high gamma coherence was more constrained to the basal ganglia nuclei. Power at three bands correlated with the motor activity of the animal, but only coherence values in the HFO and high gamma range correlated with movement. Interactions in the low gamma band did not show a direct relationship to movement.These results suggest that the motor effects of ketamine administration may be primarily mediated by the induction of coherent widespread high-frequency activity in the motor circuit of the basal ganglia, together with a frequency-specific pattern of connectivity among the structures analyzed.

Connectivity mapping of the human ECoG during a motor task with a time-varying dynamic Bayesian network

As a partially invasive and clinically obtained neural signal, the electrocorticogram (ECoG) provides a unique opportunity to study cortical processing in humans in vivo. Functional connectivity mapping based on the ECoG signal can provide insight into epileptogenic zones and putative cortical circuits. We describe the first application of time-varying dynamic Bayesian networks (TVDBN) to the ECoG signal for the identification and study of cortical circuits. Connectivity between motor areas as well as between sensory and motor areas preceding and during movement is described. We further apply the connectivity results of the TVDBN to a movement decoder, which achieves a correlation between actual and predicted hand movements of 0.68. This paper presents evidence that the connectivity information discovered with TVDBN is applicable to the design of an ECoG-based brain-machine interface.

Prediction of collision events: an EEG coherence analysis

OBJECTIVE

A common daily-life task is the interaction with moving objects for which prediction of collision events is required. To evaluate the sources of information used in this process, this EEG study required participants to judge whether two moving objects would collide with one another or not. In addition, the effect of a distractor object is evaluated.

METHODS

The measurements included the behavioural decision time and accuracy, eye movement fixation times, and the neural dynamics which was determined by means of EEG coherence, expressing functional connectivity between brain areas.

RESULTS

Collision judgment involved widespread information processing across both hemispheres. When a distractor object was present, task-related activity was increased whereas distractor activity induced modulation of local sensory processing. Also relevant were the parietal regions communicating with bilateral occipital and midline areas and a left-sided sensorimotor circuit.

CONCLUSIONS

Besides visual cues, cognitive and strategic strategies are used to establish a decision of events in time. When distracting information is introduced into the collision judgment process, it is managed at different processing levels and supported by distinct neural correlates.

SIGNIFICANCE

These data shed light on the processing mechanisms that support judgment of collision events; an ability that implicates higher-order decision-making.

Functional connectivity patterns during motor behaviour: the impact of past on present activity

Everyday behaviour often depends on the performance of multiple movements executed in a particular order. Here, the impact of task history on the neural activation patterns of motor behaviour is examined by evaluating unimanual and bimanual actions that are produced in a serial arrangement, such that switching between tasks is required. Cortical dynamics was assessed by means of EEG coherence in the beta frequency band (13-30 Hz). Results showed that although behavioural performance was not affected, switching trials induced increased coherence as compared to control (repeat) trials. This reorganization was dependent on task history and was more pronounced for unimanual than for bimanual tasks. Overall, the data illustrate that neural processing of motor behaviour within a serial arrangement integrates past and present activity, and accordingly impacts on neural efficiency.

BrainNetVis: analysis and visualization of brain functional networks

BrainNetVis is an application, written in Java, that displays and analyzes synchronization networks from brain signals. The program implements a number of network indices and visualization techniques. We demonstrate its use through a case study of left hand and foot motor imagery. The data sets were provided by the Berlin BCI group. Using this program we managed to find differences between the average left hand and foot synchronization networks by comparing them with the average idle state synchronization network.

Alpha power and coherence primarily reflect neural activity related to stages of motor response during a continuous monitoring task

Previously, EEG theta (4-6 Hz) was related to goal conflict resolution [Moore, R.A., Gale, A., Morris, P.H., Forrester, D., 2006. Theta phase locking across the neocortex reflects cortico-hippocampal recursive communication during goal conflict resolution. Int. J. Psychophysiol. 60, 260-273] in the context of theory linked with animal hippocampal theta [Gray, J.A., McNaughton, N., 2000. The Neuropsychology of Anxiety: An Enquiry into the Functions of the Septo-Hippocampal system, 2nd ed, Oxford University Press, Oxford]. Here, the hypothesis that human EEG alpha (8-12 Hz) may also be a natural analogue to animal hippocampal theta is tested. Participants engaged in a monitoring task where the object was to press a response key immediately after presentation of 4 individual, non-repeating, single integer odd digits. These were presented amongst a continuous stream of single integer digits and Xs. EEG recorded in the earlier study were reanalysed; this time extracting alpha power and coherence from the same 34 participants. Alpha had a different profile to theta and was not primarily related to goal conflict. Low alpha (8-10 Hz) coherence consistently increased at electrodes close to primary sensorimotor cortex; particularly during response execution and response inhibition. The coherence analysis revealed that high alpha (10-12 Hz) related to response execution. Supplementary analyses demonstrated widespread high alpha coherence increase during response execution, inhibition and preparation. These data were discussed within the context of motor driven 'classic alpha' and Rolandic mu. A coherence profile which differentiated response execution and response inhibition was proposed to reflect a working memory network which was activated during response execution. Also, alpha power (8-12 Hz) reduced at several central electrodes during response execution. This reflected classic Rolandic mu response. Participants displaying a predicted low alpha power trend had the fastest response times; this was linked with traditional views of low alpha's functional significance.

The neural dynamics of timed motor tasks: evidence from a synchronization-continuation paradigm

Distinct processing that integrates an accurate time scale is necessary for optimal motor behaviour. In the present study, corticocortical interactions as determined by EEG coherence were assessed in a synchronization-continuation paradigm during which subjects initially performed tapping movements in synchrony with external cues, followed by internal pacing of the target interval when the metronome was switched off. Unimanual and bimanual tasks were executed, and continuation of tapping was conducted with the same or different effector(s). The data showed an increased degree of mesial-central connectivity in the unpaced as compared to paced performance that was independent of task complexity, pointing to a general intensified demand of temporal processing when external cues are unavailable. When switching temporal information between effectors, coherence increased across the motor network. This increase depended upon preceding task complexity, and was most prominent for interhemispheric connections when performing unimanual tasks following bimanual pacing. Overall the data illustrate that timing of skilled actions can easily be transferred between effectors, although increased neural resources are required to conform to the temporal and motor constraints.

Coordination constraints during bimanual versus unimanual performance conditions

Coordinated behaviour is prominent during daily life activities in various combinations and degrees of complexity. Here the influence of coordination constraints upon motor behaviour is evaluated by contrasting two-finger tapping (in-phase and anti-phase) during bimanual and unimanual conditions. Cortical dynamics was assessed by means of EEG coherence in the beta frequency band (13-30 Hz) and included intrahemispheric, interhemispheric and midline connectivity patterns. Results showed that intrahemispheric connectivity varied strongly in the different coordination tasks, with left hemisphere dominance for bimanual and right hand coordination versus right hemisphere dominance for left hand coordination. Interhemispheric connectivity was fairly similar across coordination tasks, except for the bimanual in-phase configuration that comprised the lowest coherence scores. Midline connectivity was equivalent across coordination tasks, with exception of the bimanual anti-phase assignment that was characterized with increased coherence scores. Across connectivity regions, the lowest coherence scores were obtained for bimanual and right hand coordination performed in the in-phase mode, underlining their basic mode of functioning. Furthermore by evaluating the coordination effort, estimated by the discrepancy between the coordination task and the sum of the individual components, an increased processing for intrahemispheric and midline connections was observed, but not for interhemispheric connections, which supports the general significance of interhemispheric communication for voluntary movement. Overall the current findings indicate a dynamic modulation of functional connectivity patterns according to the coordinative context. It suggests that brain regions within a motor network flexibly couple and decouple to implement the processing requirements associated with coordinated behaviour.

Anticipatory changes in beta synchrony in the human corticospinal system and associated improvements in task performance

Synchronized oscillatory activity in the beta frequency band (13-30 Hz) can be detected in the cerebral motor cortex of healthy humans in the form of corticomuscular coherence. Elevated beta activity is associated with impaired processing of new movements and with more efficient postural or tonic contraction. Accordingly, beta activity is suppressed prior to voluntary movements, rebounding thereafter in the face of peripheral afferance. However, it remains to be established whether synchronized activity in the beta band can be up-regulated in a task-appropriate way independently of confounding changes in sensory afferance. Here we show that there is a systematic and prospective increase in beta synchrony prior to an expected postural challenge. This up-regulation of beta synchrony is associated with improved behavioural performance. We instructed nine healthy subjects to perform a reaction-time movement of the index finger in response to an imperative visual cue or to resist a stretch to the finger in the same direction. These events were preceded by congruent and less common incongruent warning cues. Beta synchrony was temporally increased when subjects were warned of an impending stretch and decreased following a warning cue signalling a forthcoming reaction-time task. Finger positions were less successfully maintained in the face of stretches and reaction times were longer when warning cues were incongruent. The results suggest that the beta state is modulated in a task-relevant way with accompanying behavioural consequences.

A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness

OBJECTIVE

We propose a theoretical framework for EEG and evoked potential studies based on the single postulate that these data are composed of a combination of waves (as this term is used in the physical sciences) and thalamocortical network activity.

METHODS

Using known properties of traveling and standing waves, independent of any neocortical dynamic theory, our simple postulate leads to experimental predictions, several of which have now been verified. A mathematical-physiological theory of "brain waves" based on known (but highly idealized) properties of cortical synaptic action and corticocortical fibers is used to support the framework.

RESULTS

Brain waves are predicted with links between temporal frequencies and the spatial distributions of synaptic activity. Such dispersion relations, which essentially define more general phenomena as waves, are shown to restrict the spatial-temporal dynamics of synaptic action with many experimental EEG consequences.

CONCLUSIONS

The proposed framework accounts for several salient features of spontaneous EEG and evoked potentials.

SIGNIFICANCE

We conjecture that wave-like behavior of synaptic action may facilitate interactions between remote cell assemblies, providing an important mechanism for the functional integration underlying conscious experience.

Changes in functional connectivity within the rat striatopallidal axis during global brain activation in vivo

The functional organization of the basal ganglia (BG) is often defined according to one of two opposing schemes. The first proposes multiple, essentially independent channels of information processing. The second posits convergence and lateral integration of striatal channels at the level of the globus pallidus (GP). We tested the hypothesis that these proposed aspects of functional connectivity within the striatopallidal axis are dynamic and related to brain state. Local field potentials (LFPs) were simultaneously recorded from multiple sites in striatum and GP in anesthetized rats during slow-wave activity (SWA) and during global activation evoked by sensory stimulation. Functional connectivity was inferred from comparative analyses of the internuclear and intranuclear coherence between bipolar derivations of LFPs. During prominent SWA, as shown in the electrocorticogram and local field potentials in the basal ganglia, intranuclear coherence, and, thus, lateral functional connectivity within striatum or globus pallidus was relatively weak. Furthermore, the temporal coupling of LFPs recorded across these two nuclei involved functional convergence at the level of GP. Global activation, indicated by a loss of SWA, was accompanied by a rapid functional reorganization of the striatopallidal axis. Prominent lateral functional connectivity developed within GP and, to a significantly more constrained spatial extent, striatum. Additionally, functional convergence on GP was no longer apparent, despite increased internuclear coherence. These data demonstrate that functional connectivity within the BG is highly dynamic and suggest that the relative expression of organizational principles, such as parallel, independent processing channels, striatopallidal convergence, and lateral integration within BG nuclei, is dependent on brain state.

Analyzing event-related EEG data with multivariate autoregressive parameters

Methods of spatio-temporal analysis provide important tools for characterizing several dynamic aspects of brain oscillations that are reflected in the human scalp-detected electroencephalogram (EEG). The search to identify the dynamic connectivity of brain signals within different frequency bands, in order to uncover the transient cooperation between different brain sites, converges at the potential of multivariate autoregressive (MVAR) models and their derived parameters. In fact, MVAR parameters provide a whole battery of so-called coupling measures including classic coherence (COH), partial coherence (pCOH), imaginary part of coherence (iCOH), partial-directed coherence (PDC), directed transfer function (DTF), and full frequency directed transfer function (ffDTF). All of these approaches have been developed to quantify the degree of coupling between different EEG recording positions, with the specific aim to characterize the functional interaction between neural populations within the cortex. This work addresses the application of MVAR models to event-related brain processes, including different statistical approaches, and reviews most relevant findings in the expanding field of coupling analysis. Finally, we present several examples of coupling patterns associated with certain types of movement imagery.

Cortico-cortical coupling in Parkinson's disease and its modulation by therapy

The role of changes in inter-regional cortical synchronization in the pathophysiology of Parkinson's disease and the mechanism of action of dopaminergic therapy and high frequency subthalamic nucleus (STN) stimulation is unclear. We hypothesized that synchronization between distributed cortical areas would correlate with parkinsonism and that changes in synchronization with treatment would correlate with improvements in parkinsonism. To this end, we recorded scalp EEG in parkinsonian patients off treatment (16 patients, 31 sides) and then separately during high frequency stimulation (HFS) of the STN (16 patients, 31 sides) and following drug treatment (12 patients, 24 sides). All recordings were made at rest to avoid the confounding effects of differences in task performance. The motor Unified Parkinson's Disease Rating Scale (UPDRS) score was determined in each state. We found that EEG-EEG coherence over approximately 10-35 Hz correlated with the severity of parkinsonism, and reductions in cortical coupling over this frequency range with both l-dopa and STN stimulation correlated with clinical improvement. These results suggest that both dopaminergic therapy and STN stimulation may support the restoration of normal cortico-cortical interactions in the frequency domain. This mechanistic similarity may underscore the strong clinical correlation between the therapeutic effects of these treatment modalities.

Dopamine depletion increases the power and coherence of β-oscillations in the cerebral cortex and subthalamic nucleus of the awake rat

Local field potentials (LFPs) recorded from the subthalamic nucleus (STN) of untreated patients implanted with stimulation electrodes for the treatment of Parkinson's disease (PD) demonstrate strong coherence with the cortical electroencephalogram over the beta-frequency range (15-30 Hz). However, studies in animal models of PD emphasize increased temporal coupling in cortico-basal ganglia circuits at substantially lower frequencies, undermining the potential usefulness of these models. Here we show that 6-hydroxydopamine (6-OHDA) lesions of midbrain dopamine neurons are associated with significant increases in the power and coherence of beta-frequency oscillatory activity present in LFPs recorded from frontal cortex and STN of awake rats, as compared with the healthy animal. Thus, the pattern of synchronization between population activity in the STN and cortex in the 6-OHDA-lesioned rodent model of PD closely parallels that seen in the parkinsonian human. The peak frequency of coherent activity in the beta-frequency range was increased in lesioned animals during periods of spontaneous and sustained movement. Furthermore, administration of the dopamine receptor agonist apomorphine to lesioned animals suppressed beta-frequency oscillations, and increased coherent activity at higher frequencies in the cortex and STN, before producing the rotational behaviour indicative of successful lesion. Taken together, these results support a crucial role for dopamine in the modulation of population activity in cortico-basal ganglia circuits, whereby dopaminergic mechanisms effectively filter out synchronized, rhythmic activity at beta-frequencies at the systems level, and shift temporal couplings in these circuits to higher frequencies. These changes may be important in regulating movement.

Functional significance of the ipsilateral hemisphere during movement of the affected hand after stroke

Previous fMRI observations have suggested increased task-related activation of the ipsilateral cerebral motor cortex in patients recovering from stroke. This is generally taken to infer an increased output from this area, although the functional relevance of this has been questioned. Here, we use directed EEG coherence to reveal whether there is increased informational flow from the ipsilateral motor cortex following motor stroke, and through correlation with degree of recovery, establish that this pattern of activity is associated with limited functional improvement. Unrecovered (n = 14), recovered (n = 11) patients and healthy subjects (n = 16) performed an isometric grip task with either hand that corresponded to 25% of individual maximum force, while EEG was recorded. For unrecovered stroke patients, most task-related information flow between the sensorimotor cortices in the low beta band of the EEG came from the ipsilateral (undamaged) hemisphere during grip with the affected hand. This was not the case when they gripped with their unaffected hand, when cortical activity was driven from the contralateral sensorimotor cortex. The latter pattern was also seen in recovered patients and controls. These findings suggest a functional role for the ipsilateral hemisphere in organizing movement of the impaired limb following stroke, but only in those patients that do not make a good functional recovery. Patients making a fuller recovery organize movement-related cortical activity from the hemisphere contralateral to movement.

Effects of muscle contraction on somatosensory event-related EEG power and coherence changes

Effects of isometric muscle contraction on amplitude and coherence changes of EEG rhythms during repetitive cutaneous electrical stimulation were analyzed in 10 right-handed subjects. Subjects received electrical stimuli at intensity above pain threshold to their right middle finger while either squeezing a rubber tube with the right index finger and thumb, or keeping their ipsilateral hand muscles relaxed. EEG was recorded using 111 closely spaced electrodes. Somatosensory stimuli were followed by reduction of the relative 8-12 and 16-24 Hz band power (at 0.2-0.4 s) in bilateral primary sensorimotor cortices (S1/M1) and medial frontal cortex, and by a subsequent increase in 16-24 Hz band power (at 0.9 s). Isometric muscle contraction strongly suppressed these band power changes. The 8-12 and 16-24 Hz mean coherence in a wide region surrounding the contralateral S1/M1 and in the medial frontal cortex showed an initial decrease, partially paralleling band power changes, and later an increase. Ipsilateral S1/M1 showed a decrease in 8-12 Hz coupling only with the central and frontal electrodes of the same hemisphere. Muscle contraction reduced all coherence changes, but enhanced the 8-12 Hz coherence between ipsilateral S1/M1 and posterior parietal cortex. Early post-stimulus decrease of oscillatory coupling between S1/M1 and premotor cortex and between S1/M1 and medial frontal cortex suggests that these cortical regions act rather independently during processing of somatosensory information, and synchronize only later when the band power in contralateral S1/M1 increases. Motor cortex activation associated with ipsilateral hand muscle contraction interferes with cortical processing of somatosensory stimuli in S1/M1 cortices.

Identifying true brain interaction from EEG data using the imaginary part of coherency

OBJECTIVE

The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction.

METHODS

We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement.

RESULTS

We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction.

CONCLUSIONS

It is possible to reliably detect brain interaction during movement from EEG data.

SIGNIFICANCE

The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.

Brain State–Dependency of Coherent Oscillatory Activity in the Cerebral Cortex and Basal Ganglia of the Rat

The nature of the coupling between neuronal assemblies in the cerebral cortex and basal ganglia (BG) is poorly understood. We tested the hypothesis that coherent population activity is dependent on brain state, frequency range, and/or BG nucleus using data from simultaneous recordings of electrocorticogram (ECoG) and BG local field potentials (LFPs) in anesthetized rats. The coherence between ECoG and LFPs simultaneously recorded from subthalamic nucleus (STN), globus pallidus (GP), and substantia nigra pars reticulata (SNr) was largely confined to slow- (∼1 Hz) and spindle- (7–12 Hz) frequency oscillations during slow-wave activity (SWA). In contrast, during cortical activation, coherence was mostly restricted to high-frequency oscillations (15–60 Hz). The coherence between ECoG and LFPs also depended on BG recording site. Partial coherence analyses showed that, during SWA, STN and SNr shared the same temporal coupling with cortex, thereby forming a single functional axis. Cortex was also tightly, but independently, correlated with GP in a separate functional axis. During activation, STN, GP, and, to a lesser extent, SNr shared the same coherence with cortex as part of one functional axis. In addition, GP formed a second, independently coherent loop with cortex. These data suggest that coherent oscillatory activity is present at the level of LFPs recorded in cortico-basal ganglia circuits, and that synchronized population activity is dynamically organized according to brain state, frequency, and nucleus. These attributes further suggest that synchronized activity should be considered as one of a number of candidate mechanisms underlying the functional organization of these brain circuits.

Changes in functional coupling patterns during bimanual task performance

Functional interaction between cortical areas may involve synchronization of activities, manifest as coherence between EEG signals. However, although EEG-EEG coherence changes when motor tasks are compared to each other or rest, there is little evidence that coherence is modulated within an action. To address this issue we used a bimanual drawer-opening task necessitating asymmetrical hand actions and comprising distinct movement phases. Pronounced modulations in EEG-EEG coherence in the beta band (>12-24 Hz) occurred with movement phase. Differences in coherence due to a switch in role of the hands were mainly observed in the alpha band (8-12 Hz). These findings suggest that inter-regional synchronization changes dynamically across task execution in line with behavioral performance.

Cortical Networks Generating Movement-Related EEG Rhythms in Alzheimer's Disease: An EEG Coherence Study

Patients with mild Alzheimer's disease (AD) present with abnormally strong values of frontal and ipsilateral central sensorimotor rhythms. The authors tested 2 working hypotheses of the related electroencephalographic (EEG) coherence: disconnection, defined as a sign of a reduced coordination within the frontoparietal and interhemispheric networks, and cooperation, defined as a reflection of the reorganization of the brain sensorimotor networks. Results showed that, compared with healthy controls, patients with mild AD had an unreactive and abnormally low interhemispheric EEG coherence and an unreactive and abnormally high frontoparietal EEG coherence. These findings support the hypothesis of an impaired mechanism of sensorimotor cortical coupling (disconnection) in mild AD.

Influence of working memory on patterns of motor related cortico-cortical coupling

Working memory is implicated in various higher-order cognitive operations. We hypothesized that the availability of a temporal representation in working memory would limit the extent of cortico-cortical coupling necessary to undertake a self-paced rhythmic movement. To this end we examined modulations in cortico-cortical interactions as determined by EEG coherence during a delay interval and subsequent movement reproduction. Right hand movement was initially paced by a metronome beat every 0.9 s, followed by a delay interval, after which hand movement was repeated in an unpaced manner. Movement reproduction after a long (22.5 s, corresponding to 25 movement cycles) compared to a short (5.4 s, corresponding to 6 movement cycles) delay interval was associated with an increased degree of functional coupling in the beta frequency band (12-30 Hz) of the left (movement-driving) hemisphere (F3-FC3, F3-C3 and F3-P3 connections) as well as mesial regions (FCz-FC3, FCz-C3 and Cz-FC3 connections) even though overall behavioral characteristics were not influenced. In addition, analysis of the EEG coherence in the delay period revealed a bilateral frontal network (F3-F4, F3-FC4, F4-FC3 and FC3-FC4 connections). Activity in the latter tended to be synchronized in the theta band (4-8 Hz) and was significantly less strong at 22.5 s than 5.4 s. These data suggest that working memory may be partly subserved by synchronization in a bilateral frontal network and may provide an intrinsic contextual influence that shapes the pattern of cortico-cortical interaction during a given task.

Structural (operational) synchrony of EEG alpha activity during an auditory memory task

Memory paradigms are often used in psycho-physiological experiments in order to understand the neural basis underlying cognitive processes. One of the fundamental problems encountered in memory research is how specific and complementary cortical structures interact with each other during episodic encoding and retrieval. A key aspect of the research described below was estimating the coupling of rapid transition processes (in terms of EEG description) which occur in separate cortical areas rather than estimating the routine phase-frequency synchrony in terms of correlation and coherency. It is assumed that these rapid transition processes in the EEG amplitude correspond to the "switching on/off" of brain elemental operations. By making a quantitative estimate of the EEG structural synchrony of alpha-band power between different EEG channels, it was shown that short-term memory has the emergent property of a multiregional neuronal network, and is not the product of strictly hierarchical processing based on convergence through association regions. Moreover, it was demonstrated that the dynamic temporal structure of alpha activity is strongly correlated to the dynamic structure of working memory.

Acoustic startle evokes bilaterally synchronous oscillatory EMG activity in the healthy human

Despite animal evidence that the reticulospinal system is of major importance to movement, this motor pathway has remained relatively inaccessible to experimentation in the human. Consequently, little is known about its function in health and disease. Here, we use the acoustic startle response to demonstrate that one type of reticulospinal activity in the human is associated with a characteristic pattern of bilateral synchronization between motor units. Surface electromyography (EMG) was recorded from upper limb muscles in 15 healthy subjects during the reflex startle to unexpected acoustic stimulation, voluntary movements mimicking the startle and during sustained voluntary tonic contraction. Frequency analysis demonstrated autospectral peaks at approximately 14 Hz in deltoid and biceps muscles only during the startle reflex. Similarly, coherence spectra of the EMG recorded between homologous proximal upper limb muscles demonstrated a peak centered approximately 12-16 Hz during reflex startles. Coherence in the 10- to 20-Hz band was significantly greater in the startle reflex than during voluntary sham startles or voluntary tonic contraction for deltoid, but not first dorsal interosseous, muscles. The coherence at 10-20 Hz between EMGs from homologous muscles represents a potential surrogate measure of reticulospinal activity that may be useful in determining the contribution of the reticulospinal system to different types of movement in health and disease.

The integration of cortical and behavioural dynamics during initial learning of a motor task

Here we test the hypothesis that frequency and topographically specific changes in the strength of functional cortico-cortical coupling occur during the acquisition of a completely new task. To this end we studied the behavioural and cortical dynamics of a bimanual multifrequency coordination pattern during which one hand moved at twice the frequency of the other hand. This pattern represents a noninherent assignment and necessitates training before appropriate interlimb decoupling takes place. Results showed that acquisition of the multifrequency task was associated with an improved behavioural output that matched specific changes in the electroencephalogram dynamics. In particular, practice of the coordination pattern was accompanied by a decrease in coherence between the primary sensorimotor regions, and over the midline area in the alpha and beta bands, respectively, along with an increase in functional interhemispheric coupling between the prefrontal areas in the gamma band. These data suggest that the strength of cortico-cortical connectivity is adaptively modified across regions and across frequencies during early learning as the functional couplings are created and optimized for the purpose of movement execution.

The importance of the dominant hemisphere in the organization of bimanual movements

The successful control of upper limb movements is an essential skill of the human motor system. Yet, the neural organization of bimanual actions remains an issue of debate. Their control can be directed from both hemispheres, or, coordinated motion might be organized from the dominant (left) hemisphere. In order to unravel the neural mechanisms of bimanual behavior, we analyzed the standard task-related and directed coherence between EEG signals picked up over the primary sensorimotor cortices in right-handed subjects during unimanual as well as bimanual in-phase (symmetrical) and anti-phase (asymmetrical) movements. The interhemispheric coherence in the beta frequency band (>13-30 Hz) was increased in both unimanual and bimanual patterns, compared to rest. During unimanual actions, the drive in the beta band from one primary sensorimotor cortex to the other was greater during movement of the contralateral as opposed to ipsilateral hand. In contrast, during bimanual actions, the drive from the dominant to the non-dominant primary sensorimotor cortex prevailed, unless task constraints induced by an external perturbation resulted in a substantial uncoupling of the hand movements, when interhemispheric coherence would also drop. Together, these results suggest that the contralateral hemisphere predominantly organizes unimanual movements, whereas coupled bimanual movements are mainly controlled from the dominant hemisphere. The close association between changes in interhemispheric coupling and behavioral performance indicates that synchronization of neural activity in the beta band is exploited for the control of goal-directed movement.

Movement rate effect on activation and functional coupling of motor cortical areas

We investigated changes in the activation and functional coupling of bilateral primary sensorimotor (SM1) and supplementary motor (SMA) areas with different movement rates in eight normal volunteers. An auditory-cued repetitive right-thumb movement was performed at rates of 0.5, 0.75, 1, 2, 3, and 4 Hz. As a control condition, subjects listened to pacing tones with no movements. Electroencephalogram (EEG) was recorded from 28 scalp electrodes and electromyogram was obtained from the hand muscles. The event-related changes in EEG band-power (ERpow: activation of each area) and correlation (ERcor: functional coupling between each pair of cortical areas) were computed every 32 ms. Modulations of ERpow and ERcor were inspected in alpha (8-12 Hz) and beta (16-20 Hz) bands. Motor cortical activation and coupling was greater for faster movements. With increasing movement rate, the timing relationship between movement and tone switched from synchronization (for 0.5-1 Hz) to syncopation (for 3-4 Hz). The results suggested that for slow repetitive movements (0.5-1 Hz), each individual movement is separately controlled, and EEG activation and coupling of the motor cortical areas were immediately followed by transient deactivation and decoupling, having clear temporal modulation locked to each movement. In contrast, for fast repetitive movements (3-4 Hz), it appears that the rhythm is controlled and the motor cortices showed sustained EEG activation and continuous coupling.

Patterns of EEG coherence, power, and contingent negative variation characterize the integration of transcendental and waking states

Long-term meditating subjects report that transcendental experiences (TE), which first occurred during their Transcendental Meditation (TM) practice, now subjectively co-exist with waking and sleeping states. To investigate neurophysiological correlates of this integrated state, we recorded EEG in these subjects and in two comparison groups during simple and choice contingent negative variation (CNV) tasks. In individuals reporting the integration of the transcendent with waking and sleeping, CNV was higher in simple but lower in choice trials, and 6-12 Hz EEG amplitude and broadband frontal EEG coherence were higher during choice trials. Increased EEG amplitude and coherence, characteristic of TM practice, appeared to become a stable EEG trait during CNV tasks in these subjects. These significant EEG differences may underlie the inverse patterns in CNV amplitude seen between groups. An 'Integration Scale,' constructed from these cortical measures, may characterize the transformation in brain dynamics corresponding to increasing integration of the transcendent with waking and sleeping.

The size of corpus callosum and functional connectivities of cortical regions in finger and shoulder movements

The correlations between the size of corpus callosum and the inter- and intra-hemispheric EEG coherence and the spatial EEG synchronization during finger and shoulder movements were analyzed in nine right-handed men. The cross-sectional surface areas of corpus callosum (CC) and of seven callosal regions were measured from the mid-sagittal slice of the anatomical MRI. Movement-related coherence between pairs of EEG electrodes overlying the central and parietal regions of both hemispheres was computed after spatially filtering EEG data by the Laplacian operator method. The spatial EEG synchronization was evaluated using omega-complexity, a novel measure which quantifies the number of independent sources of spontaneous EEG oscillations. The amplitude of coherence between the left and right S1/M1 areas after movement onset in the lower alpha band (7.8-9.8 Hz) correlated with the size of the callosal body in both types of movement. The size of the callosal body also correlated with the C3-Cz coherence in the 15.6-19.5 Hz band in finger movement, and in the 15.6-23.5 Hz band in shoulder movements. The size of the rostral, anterior intermediate and posterior intermediate truncus of CC correlated with omega-complexity in both types of movements indicating more foci of synchronized EEG oscillations in subjects with a large callosal truncus. The results suggest that the size of callosal truncus which is known to connect the primary sensorimotor and the supplementary motor areas of both hemispheres contributes to the coupling of EEG oscillations during voluntary finger and shoulder movements.

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data.

Cortical connectivity during word association search

Cortical connectivity was studied in tasks of generating the use of words in comparison with reading aloud the same words. These tasks were used earlier in PET and high density ERP recordings studies (Posner and Raichle, 1997; Abdullaev and Posner, 1998), in which both the functional anatomy and the time course of cortical areas involved in word processing were described. The wavelet transforms of ERP records and the calculation of correlations between wavelet curves were used to reveal connections between cortical areas. Three stages of intracortical communications while task performance were found. These were: (1) the connections between right and left frontal and central areas which preceded stimulus delivery and persisted up to 180 ms after it; (2) the network connecting right and left frontal with left posterior temporal-parietal junction at 280-450 ms; and (3) communications between left and right temporal zones in 550-800 ms. The data are in good agreement with results of previous PET and ERP studies and supply the earlier findings with circuitry of cortical information transfer.